API Updates: fleshing out RAG APIs, introduce "llama stack" CLI command (#51)

* add tools to chat completion request

* use templates for generating system prompts

* Moved ToolPromptFormat and jinja templates to llama_models.llama3.api

* <WIP> memory changes

- inlined AgenticSystemInstanceConfig so API feels more ergonomic
- renamed it to AgentConfig, AgentInstance -> Agent
- added a MemoryConfig and `memory` parameter
- added `attachments` to input and `output_attachments` to the response

- some naming changes

* InterleavedTextAttachment -> InterleavedTextMedia, introduce memory tool

* flesh out memory banks API

* agentic loop has a RAG implementation

* faiss provider implementation

* memory client works

* re-work tool definitions, fix FastAPI issues, fix tool regressions

* fix agentic_system utils

* basic RAG seems to work

* small bug fixes for inline attachments

* Refactor custom tool execution utilities

* Bug fix, show memory retrieval steps in EventLogger

* No need for api_key for Remote providers

* add special unicode character ↵ to showcase newlines in model prompt templates

* remove api.endpoints imports

* combine datatypes.py and endpoints.py into api.py

* Attachment / add TTL api

* split batch_inference from inference

* minor import fixes

* use a single impl for ChatFormat.decode_assistant_mesage

* use interleaved_text_media_as_str() utilityt

* Fix api.datatypes imports

* Add blobfile for tiktoken

* Add ToolPromptFormat to ChatFormat.encode_message so that tools are encoded properly

* templates take optional --format={json,function_tag}

* Rag Updates

* Add `api build` subcommand -- WIP

* fix

* build + run image seems to work

* <WIP> adapters

* bunch more work to make adapters work

* api build works for conda now

* ollama remote adapter works

* Several smaller fixes to make adapters work

Also, reorganized the pattern of __init__ inside providers so
configuration can stay lightweight

* llama distribution -> llama stack + containers (WIP)

* All the new CLI for api + stack work

* Make Fireworks and Together into the Adapter format

* Some quick fixes to the CLI behavior to make it consistent

* Updated README phew

* Update cli_reference.md

* llama_toolchain/distribution -> llama_toolchain/core

* Add termcolor

* update paths

* Add a log just for consistency

* chmod +x scripts

* Fix api dependencies not getting added to configuration

* missing import lol

* Delete utils.py; move to agentic system

* Support downloading of URLs for attachments for code interpreter

* Simplify and generalize `llama api build` yay

* Update `llama stack configure` to be very simple also

* Fix stack start

* Allow building an "adhoc" distribution

* Remote `llama api []` subcommands

* Fixes to llama stack commands and update docs

* Update documentation again and add error messages to llama stack start

* llama stack start -> llama stack run

* Change name of build for less confusion

* Add pyopenapi fork to the repository, update RFC assets

* Remove conflicting annotation

* Added a "--raw" option for model template printing

---------

Co-authored-by: Hardik Shah <hjshah@fb.com>
Co-authored-by: Ashwin Bharambe <ashwin@meta.com>
Co-authored-by: Dalton Flanagan <6599399+dltn@users.noreply.github.com>

llama_toolchain/inference/client.py

@@ -6,12 +6,15 @@
 
 import asyncio
 import json
-from typing import AsyncGenerator
+from typing import Any, AsyncGenerator
 
 import fire
 import httpx
+from pydantic import BaseModel
 from termcolor import cprint
 
+from llama_toolchain.core.datatypes import RemoteProviderConfig
+
 from .api import (
     ChatCompletionRequest,
     ChatCompletionResponse,
@@ -23,13 +26,16 @@ from .api import (
 from .event_logger import EventLogger
 
 
-async def get_client_impl(base_url: str):
-    return InferenceClient(base_url)
+async def get_client_impl(config: RemoteProviderConfig, _deps: Any) -> Inference:
+    return InferenceClient(config.url)
+
+
+def encodable_dict(d: BaseModel):
+    return json.loads(d.json())
 
 
 class InferenceClient(Inference):
     def __init__(self, base_url: str):
-        print(f"Initializing client for {base_url}")
         self.base_url = base_url
 
     async def initialize(self) -> None:
@@ -46,7 +52,9 @@ class InferenceClient(Inference):
             async with client.stream(
                 "POST",
                 f"{self.base_url}/inference/chat_completion",
-                data=request.json(),
+                json={
+                    "request": encodable_dict(request),
+                },
                 headers={"Content-Type": "application/json"},
                 timeout=20,
             ) as response: